• Journal of Information Technology Services
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• v.12 no.2
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• pp.349-359
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• 2013

Recently, smart phones have been widely used in the world. Android phones especially provide existing mobile phone features as well as capability of running enterprise applications and web applications by using services. However, such a linkage has limitations to use Android phones as client devices, there is difficulties in providing services by utilizing characteristics of Android. To solve this problem, we need to invoke services by each other. Currently, the Android platform currently supports inter-process communication IPC. However, there is a limitation that Android services just can invoke remote calls. In this paper, we propose a framework to invoke Android services in java environments. For doing this, we propose methods to make services public and to invoke services in using remote calls and communication methods between java environments and Android.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.351-356
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• 2016

In recent years, as smartphones with Android platforms expand, the number of Android applications increases. Android applications implement Java and XML to compose the user interface, among other things. Between Java and XML, various problems may occur. Nonetheless, static analysis research and tools are not sufficient. In this paper we will list the problems which may occur between Java and XML. Subsequently, we will propose a detection method for them. Using the proposed technique, we found 172 Android-specific problems and 35 performance drop issues in 150 Android applications in the Google Play Store. We would like to contribute to research into static analysis and software quality improvement.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.169-177
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• 2010

As expectations about success of smart phones that install Android, an open mobile platform which was developed by Google, are increasing, the development of applications based on the Android has attracted a lot of interest. Especially, game applications have been well received by users. In this paper, we develop an application based on the Android for curling which was adopted as a competitive sport in the Winter Olympic Games. Curling is a sport game played by two teams. The rules of the game are simple, but it is an intelligent one that requires various strategies for victory. In this paper, the curling game based on the Android provides functions, such as pitching, sweeping, collision, and foul handling, that are required in real curling game by using technologies, such as touch screen or accelerometer sensor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2180-2197
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• 2019

With the proliferation of the Android malicious applications, malware becomes more capable of hiding or confusing its malicious intent through the use of code obfuscation, which has significantly weaken the effectiveness of the conventional defense mechanisms. Therefore, in order to effectively detect unknown malicious applications on the Android platform, we propose DroidVecDeep, an Android malware detection method using deep learning technique. First, we extract various features and rank them using Mean Decrease Impurity. Second, we transform the features into compact vectors based on word2vec. Finally, we train the classifier based on deep learning model. A comprehensive experimental study on a real sample collection was performed to compare various malware detection approaches. Experimental results demonstrate that the proposed method outperforms other Android malware detection techniques.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.403-414
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• 2011

Recently, smart phones based on Android platform have been widely used, and lots of applications have been developed. Data generated from an application are frequently transferred to other applications. Therefore, a method that can easily transfer or share meta-data among applications is required. Generally meta-data created by android applications are java objects. The android platform uses clipboard, intent and content provider in order to transfer data among the applications. However, those ways are designed to transfer data as a record. So these methods have to marshall the object to a record and unmarshall the record to an object. In this paper, we designed and implemented the MetaService which can transfer any type of object made by applications. When the MetaService is used, we can reduce complex implementations such as clipboards and content providers and we can reduce many bugs. Therefore, we can make the applications simple and increase productivity.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.234-243
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• 2017

With the development of smartphone technologies enable photoplethysmogram (PPG) acquisition by camera and heart rate (HR) measurement. This papers presents improved algorithm to extract HR from PPG signal recorded by smartphone camera and to develop real-time PPG signal processing Android application. 400 video samples recorded by Samsung smartphone camera are imported as input data for further processing and evaluating algorithm on MATLAB. An optimized algorithm is developed and tested on Android platform with different kind of Samsung smartphones. To assess algorithm's performance, medical device Beurer BC08 is used as reference. According to related works, accuracy parameters includes 90% number of samples that has relative errors less than 5%, Person correlation (r) more than 0.9, and standard estimated error (SEE) less than 5 beats-per-minutes (bpm).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.213-221
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• 2013

According to the rapid growth of the number of SNS(Social Networking Service) applications based on Android OS, the importance of its security is also raised. Especially, many applications using KaKaoTalk platform has been released in these days, and these are top ranked in the relative markets. However, security issues on SNS applications have not been resolved clearly. Therefore, it is crucial to provide means to cope with the security threats posed by code-segment modification in the development stage of Android OS based SNS applications. In this paper, we analyze the security threats by modifying SNS application code segments and suggest effective security techniques.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.421-432
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• 2013

The changes in the game platform is appeared since the advent of smart-phones. Apple's iOS or Google's Android platform is gradually expanding their territories in the mobile game area. Android's platform fragmentation and the absence of game development framework act as barriers for game developments. In the development of game applications on the smart-phone, the standardized development procedures under game framework can achieve the productivity improvement. In this paper, we propose a new design pattern suitable for the design of a framework for new areas of application through the expansion of existing framework. The design and implementation of the Android game development framework is presented by taking advantage of existing design patterns and a proposed pattern. Also we propose the standardized development procedure of game applications under the proposed framework.